A family of smoothing algorithms for electron and other spectroscopies based on the Chebyshev filter

Smoothing is a useful tool to improve the signal-to-noise ratio of spectroscopic data. This paper reports a new family of smoothing formulas, the Chebyshev filters, which are derived approaching the original data to a polynomial and using the mini–max principle, that is, keeping the maximum error do...

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Veröffentlicht in:Thin solid films Jg. 513; H. 1; S. 72 - 77
Hauptverfasser: López-Camacho, E., García-Cortés, A., Palacio, C.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Lausanne Elsevier B.V 14.08.2006
Elsevier Science
Schlagworte:
Chebyshev filters
Condensed matter: electronic structure, electrical, magnetic, and optical properties
Condensed matter: structure, mechanical and thermal properties
Electronic structure and electrical properties of surfaces, interfaces, thin films and low-dimensional structures
Exact sciences and technology
Optical absorption spectroscopy
Physics
Smoothing algorithms
Surfaces and interfaces; thin films and whiskers (structure and nonelectronic properties)
X-ray photoelectron spectroscopy
Optical absorption spectroscopy
Smoothing algorithms
Chebyshev filters
X-ray photoelectron spectroscopy
Lanthanum oxides
Smoothing methods
Sodium oxides
Inorganic compounds
Tetragonal lattices
Fitting
Cut-off
Transfer functions
Transition element compounds
Theoretical study
Signal-to-noise ratio
Spectral window
Tungsten oxides
Rare earth compounds
Algorithms
Absorption spectra
Optical absorption
X-ray photoelectron spectra
ISSN:0040-6090, 1879-2731
Online-Zugang:Volltext
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Zusammenfassung:Smoothing is a useful tool to improve the signal-to-noise ratio of spectroscopic data. This paper reports a new family of smoothing formulas, the Chebyshev filters, which are derived approaching the original data to a polynomial and using the mini–max principle, that is, keeping the maximum error down to a minimum, as fitting criterion. The properties of the filters are studied analyzing their associated transfer functions in the frequency domain. This leads us to the concept of spectral window and spectral window width as tool and parameter, respectively, to remove the high frequency noise components accompanying the experimental data. Also, simple criteria to choose the appropriate width of the spectral windows are put forward. The behaviour of the filters is easy to understand and the filters are fast and simple to use and to program. Finally the proposed smoothing algorithms have been tested using synthetic data as well as X-ray photoelectron spectra and optical absorption spectra.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0040-6090
1879-2731
DOI:10.1016/j.tsf.2006.01.024